Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

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International Journal of Advanced Network, Monitoring and Controls

Xi'an Technological University

Subject: Computer Science, Software Engineering

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eISSN: 2470-8038

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VOLUME 2 , ISSUE 3 (September 2017) > List of articles

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

Xinyu Zhang / Botu Xue / Guanghu Sui / Jianjiang Cui *

Keywords : Distribution estimation algorithm, Probability vector, Blood indices, Parallel algorithm, Cloud computing

Citation Information : International Journal of Advanced Network, Monitoring and Controls. Volume 2, Issue 3, Pages 20-26, DOI: https://doi.org/10.1109/iccnea.2017.87

License : (CC BY-NC-ND 4.0)

Published Online: 10-April-2018

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ABSTRACT

To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to update the population, the algorithm increases the convergence speed and enhances the searching ability, compared to GA. In the experiment of mining association, rules in blood indices data, PBIL algorithm performs better not only in running time, convergence speed, but also achieve better searching results. Meanwhile, this paper proposed a parallel algorithm for association rule mining based on PBIL and designed a system architecture based on cloud computing for blood indices analysis, providing a good example to apply the new algorithm to cloud computing.

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